Blood Metal Analysis of Plasmas from Donors with and without SARS-CoV-2 using Laser-Induced Breakdown Spectroscopy and Logistic Regression: An Interview with Noureddine Melikechi

The sudden outbreak of a pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also known as Covid-19) in December 2019 led to the death of over six million people worldwide. As the Covid-19 virus propagated, a team of scientists began to search for a potential correlation between metal levels in blood and Covid-19 infection. This was primarily performed using samples from donors with various levels of severity to Covid-19 infection. Using logistics regression on laser-induced breakdown spectroscopy (LIBS) spectra of plasma samples collected pre- and post- Covid-19 pandemic from donors known to have developed various levels of antibodies to the SARS-Cov-2 virus, University of Massachusetts physics professor Nourddine Melikechi’s research team has shown that relying on the levels of sodium (Na), potassium (K), and magnesium (Mg) together is more efficient at differentiating the two types of plasma samples than any single blood metal alone. Melikechi, corresponding author for the paper that resulted from this research, spoke to Spectroscopy magazine about his team’s findings.

In your paper (1), you discussed using laser-induced breakdown spectroscopy (LIBS) to search for potential associations between levels of blood metals in plasma samples collected before December 2019—in other words pre-pandemic (used as healthy controls)—and post-Covid pandemic (known to have been infected with SARS-CoV-2) irrespective of the severity of the Covid-19 disease. What inspired this research?

The emergence of Covid-19 in December 2019 marked a singular global health event that disrupted the lives of millions of people and presented an unexpected challenge worldwide. Initially, the SARS-CoV-2 virus primarily affected the lungs. However soon several distinct complications, extending beyond the respiratory system, were reported by health professionals. These included liver dysfunction, headaches, loss of smell, inflammation of the heart muscle, kidney injury, and blood clotting abnormalities in some cases. In parallel, as the virus was spreading, new studies suggested that changes in levels of sodium in the blood may predict the severity status of Covid-19 patients; others suggested that zinc could hamper the SARS‑CoV‑2 virus from multiplying by interfering with its ability to make copies of itself. In some weird way, the sudden emergence of the Covid-19 pandemic and the seemingly relatively strong association of blood metals and the health status Covid-19 patients inspired us to investigate whether certain metals present in the blood have a connection to Covid-19, and if they do, what might it be.

What is the hypothesis regarding levels of metals in plasma as related to SARS-CoV-2 infection?

Based on several published reports that associated various blood metals to Covid-19, we hypothesized that, compared to those acquired pre-pandemic, the levels of blood metals of a donor who tested positive for Covid-19 may have undergone fundamental changes. We expected that levels of some blood metals of donors who have never been exposed to the SARS-CoV-2 virus to differ from those who have. We designed a spectroscopic study based on measuring the LIBS spectra of blood plasma samples of these two groups of donors. We compared our spectroscopic results to those of two independent diagnostics tools, namely Real-Time Reverse Transcriptase–Polymerase chain reaction (RT-PCR) in nasal swab samples described in our paper (1) and the IgG antibody values in the blood plasma samples.

Other than the LIBS technique being used, does your work differ from what has been previously done by yourself or others?

LIBS is a multi-elemental analytical technique that requires no or very little sample preparation. Using LIBS, we have measured simultaneously several elements present in the blood plasma of the two types of donors. For each sample, we acquired a rich spectrum that contains information about the levels of blood metals. Other research groups have used other techniques to measure levels of bio-metals in plasmas such as atomic absorption spectrometry, X-ray fluorescence spectroscopy, and ICP-MS. Of these, ICP-MS is the technique that can provide rich elemental information. However, it calls for a higher level of experimental complexity while other analytical techniques suffer from limitations such as the lack of the possibility of simultaneously measuring accurately a broad range of elements. In terms of analysis, our study differs from others in that we focused not only on the levels of individual elements but searched also for their potential collective association with the Covid-19 status (positive or negative) of the donors. This was accomplished by comparing the elemental composition of blood collected pre-pandemic to that of donors with Covid-19 using logistic regression. Finally, we tested our approach on blind blood plasma samples.

Briefly state your findings.

We have shown that a combination of multiple elements, principally potassium, sodium, and magnesium, yields higher classification accuracies of the blood plasma samples than any of these elements considered separately. In other words, the combined spectral signatures of these elements better distinguishes the two types of blood plasma samples. The ratio of levels of potassium and sodium and to some extent their association with levels of magnesium yields excellent differentiation of the samples acquired from donors pre-pandemic and those known to have had covid-19. This result was obtained using a multi-element machine learning approach that allows for the emergence of combinations of elements that might get drowned in the variability between individuals. We found that the ratio of the sodium to potassium ratio, controlled by the Na, K-ATPase, to be disturbed in donors who contracted Covid. This result may be in line with the findings of other research groups that show that SARS-CoV-2 virus impacts the Na, K-ATPase in the lungs. In addition, we used logistic regression to identify the features that differentiate the two types of blood plasma samples. This was very useful as it directed us to look at the spectroscopic data in a new light. Without the use of machine learning, it would have been challenging to identify the association of the most relevant spectral elemental features that can differentiate optimally the two types of blood plasma samples.

Do your findings correlate with what you had hypothesized?

To a significant degree, our results supported our initial hypothesis. However, we didn't anticipate the specific type of inter-elemental relationship that would best classify the blood plasma samples. It was also surprising to discover a strong correlation between the sodium-to-potassium ratio and the Covid-19 status of the donors.

Was there anything particularly unexpected that stands out from your perspective?

Yes, there was. In addition to the strong correlation, I just mentioned, we were surprised that more than 80% of the blind samples tested positive for Covid-19. It turned out that these were collected post-pandemic. The prevalence of positive results underscores the widespread nature of the virus during the collection time.

Were there any limitations or challenges you encountered in your work?

Conducting this study posed several challenges. First, we had blood samples from 150 donors, 46 samples were collected prior to the emergence of the pandemic, while 64 samples were confirmed by RT-PCR to be positive to Covid-19, the rest were blind to us during the LIBS measurements. This is a relatively low number of samples to conduct comfortably machine learning tests. The second challenge was to maintain consistency in the handling, transport, and storage of all blood samples both before their arrival at our laboratory and during their processing within our research facility and to reduce measurement uncertainties. Finally, obtaining tnegative blind samples during the pandemic added another layer of complexity to our study design. Despite these challenges, we obtained meaningful insights.

What best practices that can you recommend in this type of analysis for both instrument parameters and data analysis?

Paying attention to details! It is important to carefully design the experiments to reduce potential systematic uncertainties, with one key step being the randomization of samples before acquiring spectra. Equally significant is to understand how uncertainties in the measurements impact machine learning algorithms. This helps to avoid drawing erroneous conclusions.

Can you please summarize the feedback that you have received from others regarding this work?

This study was published only recently. The only feedback we have received this far is from a small group of researchers, typically pursuing disease diagnostics using lasers. Their feedback has been encouraging in terms of the potential impact on the development of disease screening tests. Time will tell how this work will be received and whether it will catalyze further studies in the area of the relationship between elemental composition and diseases and possibly in the development of liquid biopsy techniques.

Do you imagine these techniques to be adaptable for other disease states, or perhaps work with different biological tissues other than blood? Or other blood components (red or white cells, platelets)?

The spectroscopic approach we employed for this study can be extended to a wide array of applications and diseases. Our previous work on Alzheimer's disease and various cancers has demonstrated the versatility and applicability of our method. Moreover, other research groups have also successfully implemented similar approaches as well as imaging techniques, as detailed in a book (2). Regarding specimen types, we worked on biomedical fluids because our focus is to develop liquid biopsy techniques. I see no reason why other blood components cannot be investigated.

What are the next steps in this research?

In addition to the results published, we have observed a relatively strong correlation between the levels of the IgG antibodies and ratios of the levels of elements, particularly that of sodium to potassium. The next step is to finalize the analysis and submit our findings for publication. Ideally, we would like to conduct a study with a larger sample size that was available to us for this first one. In addition, I suspect that we can learn quite a lot from a longitudinal study. LIBS analysis of blood plasma of donors who have tested positive for Covid-19 over a period of few months will yield additional insights into the onset of Covid-19 and its remission. A longitudinal study performed with a larger blood plasma sample size may provideindications as to whether the collective association of two or more elements can not only offer a high degree of differentiation between the two types of blood samples but also insights into the underlying biomedical processes that takes place when an individual becomes positive to Covid-19.

References

1. Melikechi N.; Adler H. G.; Safi A.; Landis J.E.; Pourkamali-Anaraki F.; Eseller K. E.; Berlo K.; Bonito D.; Chiklis G. R.; Xia W. Blood Metal Analysis of Plasmas from Donors with and without SARS-CoV-2 using Laser-Induced Breakdown Spectroscopy and Logistic Regression. Biomed. Opt. Express 2023, 15 (1), 446-459. DOI: 10.1364/BOE.513558

2. N. Melikechi, Editor, Optical Spectroscopy and Imaging: Fundamentals, Progress and Challenges, World Scientific Publishing Inc., 2023.

Noureddine Melikechi is a Professor of Physics and the Dean of the Kennedy College of Sciences at the University of Massachusetts Lowell. Professor Melikechi worked on wide-range of scientific issues related to multi-photon-matter interactions including precise pulsed laser spectroscopy, non-linear optics, and laser spectroscopy of complex systems. As a member of NASA’s Mars missions, he contributed to the analysis of laser-induced spectroscopy data collected by the ChemCam and the SuperCam instruments on board the Curiosity and Perseverance rovers. In recent years, Professor Melikechi’s has been working on the development of minimally invasive laser-based approaches for the early detection of cancers and Alzheimer’s. Professor Melikechi is a Fellow of the American Association for the Advancement of Science, Fellow of the American Physical Society, and Fellow of the Optica. He received his Diplôme d'Études Supérieures in Physics from the University of Sciences and Technology Houari Boumediene, Algeria, and his D.Phil., in Physics, from the University of Sussex.